class_docstr: Suggested backoff chain; includes at least on of each
  type of major sequential backoff class from backoff.py
  
  ### Putting it all together
  ### BETA Version of the Backoff Lemmatizer AKA BackoffLatinLemmatizer
  ### For comparison, there is also a TrainLemmatizer that replicates the
  ###    original Latin lemmatizer from cltk.stem
class_docstr_tok: ["Suggested","backoff","chain",";","includes","at","least","on","of","each","type","of","major","sequential","backoff","class","from","backoff.py","#","#","#","Putting","it","all","together","#","#","#","BETA","Version","of","the","Backoff","Lemmatizer","AKA","BackoffLatinLemmatizer","#","#","#","For","comparison",",","there","is","also","a","TrainLemmatizer","that","replicates","the","#","#","#","original","Latin","lemmatizer","from","cltk.stem"]
code: def __init__(
      self,
      train: List[list] = None,
      seed: int = 3,
      verbose: bool = False,
  ):
      self.models_path = os.path.normpath(
          os.path.join(
              CLTK_DATA_DIR,
              "lat",
              "model",
              "lat_models_cltk",
              "lemmata",
              "backoff",
          )
      )
  
      missing_models_message = "LatinBackoffLemmatizer requires the ```latin_models_cltk``` to be in cltk_data. Please load this corpus."
  
      try:
          self.train = open_pickle(
              os.path.join(
                  self.models_path, "latin_pos_lemmatized_sents.pickle"
              )
          )
          self.LATIN_OLD_MODEL = open_pickle(
              os.path.join(
                  self.models_path, "latin_lemmata_cltk.pickle"
              )
          )
          self.LATIN_MODEL = open_pickle(
              os.path.join(self.models_path, "latin_model.pickle")
          )
      except FileNotFoundError as err:
          raise type(err)(missing_models_message)
  
      self.latin_sub_patterns = (
          latin_sub_patterns  # Move to latin_models_cltk
      )
  
      self.seed = seed
      self.VERBOSE = verbose
  
      (
          self.pos_train_sents,
          self.train_sents,
          self.test_sents,
      ) = self._randomize_data(self.train, self.seed)
      self._define_lemmatizer()
  
file_path: cltk/src/cltk/lemmatize/lat.py
imports: import os
  import re
  from typing import List
  from cltk.lemmatize.backoff import DefaultLemmatizer, DictLemmatizer, IdentityLemmatizer, RegexpLemmatizer, UnigramLemmatizer
  from cltk.utils import CLTK_DATA_DIR
  from cltk.utils.file_operations import open_pickle
label_desc: Use image node_id 1 to create a new LatinBackoffLemmatizer object  with example: obj = LatinBackoffLemmatizer(train, seed, verbose)